AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) vs NVIDIA Jetson AGX Thor

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Split result: AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) is faster in 2 and NVIDIA Jetson AGX Thor in 4 of 6 like-for-like comparisons.

	AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S)	NVIDIA Jetson AGX Thor
Best object detection	476 FPS B 2026 (year only)	719 FPS B undated
Power	120 W spec	130 W spec
Perf / W	3.97 FPS/W spec	5.53 FPS/W spec
Price	n/a	$3499 list
Workloads with data	2 of 7	2 of 7

Best published object detection result per platform (may be from different like-for-like groups — see data). n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

✓ Like-for-like: model-size class nano (YOLO-n), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	719 FPS inference_time · b=1	YOLO26n FP16 · Ultralytics TensorRT · nano (YOLO-n)	B	130 W spec platform spec envelope (not measured with this result)	Ultralytics docs benchmark table undated
AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S)	476 FPS inference_time · b=1	YOLO26n FP32 · Ultralytics 8.4.165 ONNX Runtime MIGraphX EP · nano (YOLO-n)	B	120 W spec platform spec envelope (not measured with this result)	Ultralytics docs: AMD ROCm/MIGraphX integration benchmark 2026 (year only)

instance segmentation

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No published instance segmentation results for AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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No published pose estimation results for AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

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No published image classification results for AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

semantic segmentation

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No published semantic segmentation results for AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

speech-to-text

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No published speech-to-text results for AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

✓ Like-for-like: model-size class LLM 5–14B, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	45.00 tok/s tok/s gen, concurrency 1 · b=1	Qwen2.5-VL 7B n/s on page · NVIDIA (vLLM/TensorRT-LLM per page) · LLM 5–14B	D	130 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks undated
AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S) CPU-only	11.37 tok/s generation_throughput · b=1	DeepSeek R1 14b as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue) · LLM 5–14B	C	140 W measured reported in result source — measured	Jeff Geerling ai-benchmarks README (Findings tables) undated

✓ Like-for-like: model-size class LLM >40B, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S)	47.80 tok/s generation_throughput · b=1	Qwen3.8-Flash-Next 125B (MoE, 6B active) not stated · gfx1151 native engine with speculative decoding (not Ollama) · LLM >40B	C	120 W spec platform spec envelope (not measured with this result)	Adam Taylor (Adiuvo Engineering) (manual extraction) undated
NVIDIA Jetson AGX Thor	15.00 tok/s generation_throughput · b=1	Nemotron 3 Super 120B-A12B NVFP4 · vLLM · LLM >40B	C	130 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) undated

✓ Like-for-like: model-size class LLM 15–40B, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	72.60 tok/s generation_throughput · b=1	Qwen3-30B-A3B INT4 GPTQ · Edge-LLM · LLM 15–40B	C	130 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) undated
AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S)	47.50 tok/s generation_throughput · b=1	Qwen3-Coder 30B (MoE, 3.3B active) not stated per model · Ollama (OpenAI-compatible endpoint) · LLM 15–40B	C	120 W spec platform spec envelope (not measured with this result)	Adam Taylor (Adiuvo Engineering) (manual extraction) undated

✓ Like-for-like: model-size class LLM ≤4B, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	122 tok/s generation_throughput · b=1	Qwen3-VL-2B NVFP4 · vLLM · LLM ≤4B	C	130 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) undated
AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S)	88.14 tok/s generation_throughput · b=1	Llama 3.2:3b as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue) · LLM ≤4B	C	133 W measured reported in result source — measured	Jeff Geerling ai-benchmarks README (Findings tables) undated

✓ Like-for-like: model-size class LLM >40B, batch unknown (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Ryzen AI Max+ 395 / PRO 395 (Strix Halo, Radeon 8060S)	62.09 tok/s tg128 · b=unknown	Qwen3-Next 80B-A3B UD-Q4_K_XL · llama.cpp Vulkan RADV b10687 · LLM >40B	C	120 W spec platform spec envelope (not measured with this result)	StrixHaloGuide evidence (llama-bench, 20 repeats) 2026-10
NVIDIA Jetson AGX Thor	4.40 tok/s tg · b=unknown	70B-class LLM (Q4) ~Q4 · as reviewed (Ollama/llama.cpp class) · LLM >40B	C	100 W measured reported in result source — measured	vminstall.com review 2026 (year only)

How to read these numbers

Every number is labelled. Confidence: A MLPerf closed, audited · B documented third-party method · C community / review · D vendor-published, not independently verified · E estimate. Power basis: measured with the result · spec vendor spec/envelope · power n/a not published.

Machine-readable: /find.json (see llms.txt); full tables are in “Show data”. Confidence grades: A audited MLPerf closed · B documented third-party · C community · D vendor-published · E estimate. Unknown values are shown as unknown, never estimated. Generated 2026-10-16 from public sources.